Top AI Engineer Jobs

Develop and implement automation for ML/LLM integrations and data pipelines to support incident response and automated malware analysis. Build ingestion, transformation, monitoring, API integrations, and scale automation from pilot to production while ensuring data quality and documenting solutions.

Design, build, and maintain end-to-end integrations between Commures platform and third-party healthcare systems (EHRs/EMRs). Implement scalable, reliable solutions using LLMs and modern cloud tooling, ensure HL7/FHIR and HIPAA compliance, troubleshoot production issues, mentor junior engineers, and drive integration platform architecture and monitoring.

The Data Engineer will develop and optimize data pipelines for LLMs, ensuring high-quality healthcare datasets while collaborating with data scientists on model requirements.

The Technology Program Quality Assurance Engineer enhances quality engineering in veterinary practice by leveraging technology for compliance, automation, and process improvement in quality management systems.

Lead design and ownership of an AI-native web platform: web framework, design system, CMS, CI/CD, infrastructure, rendering and edge delivery. Define architecture and agentic SDLC, build evaluation guardrails, mentor engineers, and drive platform-wide technical alignment and migrations.

Build and scale web platform infrastructure (CI/CD, deployment automation, secrets management, edge delivery) for databricks.com. Implement automated accessibility testing and centralized consent management, unify frameworks into a shared design system, and operate within an AI-native, agent-assisted SDLC to drive platform features to production.

Design, build, and operate scalable data and AI platform capabilities. Create reusable abstractions, templates, and services for data pipelines and products. Integrate Generative AI for discovery and automation, ensure data quality, lineage, observability, security, and support cross-functional analytics and applied-AI teams.

The Software Engineer, AI will develop intelligent systems for financial workflows, utilizing LLMs and other technologies to enhance bookkeeping and data processing for agriculture businesses.

Develop and optimize end-to-end data pipelines for autonomous driving, ensure data quality, and support model training through efficient data management processes.

Design, build, and optimize scalable AI-enabled application features and services. Integrate ML models and generative AI, ensure secure and test-driven implementations, troubleshoot AI performance, mentor engineers, and drive AI architecture, CI/CD, and best practices across teams.

Partner-facing engineer who designs, builds, evaluates, debugs, and launches high-utility plugins for ChatGPT and Codex. Own partner technical journeys, write prototypes and production code, review architectures for security/privacy/reliability, run evaluations, and improve platform APIs, SDKs, docs, and tooling to support smooth launches and ongoing maintenance.

Define long-term architecture and technical strategy for Target's enterprise ML/Ops platform. Design cloud-native, scalable, secure Kubernetes-based platforms; establish ML lifecycle, deployment, governance, observability, and responsible AI standards; evaluate technologies; mentor engineers; and partner with infrastructure, security, and product teams to modernize platform capabilities.

The role involves developing AI and machine learning solutions to improve organizational efficiency, ensuring user-focused system modernization and compliance with cybersecurity standards.

Design and implement end-to-end AI/ML software solutions to modernize client systems. Build developer-focused tools and prototypes, apply best practices for software workflows, and collaborate to refine experimental tooling while considering ecosystem and future enhancements.

Design, build, and operate large-scale production systems and integrate diverse technologies. Develop AI/ML-enabled end-to-end solutions on AWS, manage Kubernetes deployments, and implement observability. Lead technical initiatives, support policy/governance, and work within TS/SCI polygraph security requirements.

Partner with Sales to design and demo AI-powered, data-driven solutions for life sciences clients using Komodo's Healthcare Map. Run live no-code analyses, build reusable demo assets, navigate AI governance and procurement, quantify ROI, mentor junior SEs, and feed product/AI roadmap input.

Lead design and delivery of scalable Data and AI solutions, mentor engineering teams, drive GenAI proof-of-concepts, align technical strategy with business goals, and influence cross-functional stakeholders.

Build, deploy, and maintain internal AI-powered applications and orchestration pipelines. Re-engineer business workflows for automation, define standards for reliability and observability, collaborate with IT/Security/DevOps, and mentor team members to drive company-wide AI adoption and measurable efficiency gains.

The Lead Software Engineer will mentor a frontend team while actively contributing to development, focusing on quality and collaboration with product and design partners.

The role involves developing and implementing applications and databases, ensuring application performance, providing software development expertise, and mentoring less experienced staff.

Build and maintain secure RESTful and event-driven APIs and MCP server implementations to allow AI agents to interact with enterprise platforms (ServiceNow, Okta, ERP). Implement authentication (OAuth2/OIDC), API gateway policies, audit logging, and monitoring. Collaborate with AI and governance teams, document integrations, and ensure secure, reliable, auditable agentic workflows.

Design and implement scalable AI-driven data solutions across cloud platforms (Snowflake/Databricks/BigQuery). Prototype and productionize LLM-based systems for dynamic SQL, document and vector search, and semantic retrieval. Build vector search (OpenSearch), metadata/catalog layers, and governed AI data pipelines. Advise engineering leadership on technology direction, contribute code and architecture, and mentor global engineering teams.

Design, build, and deliver scalable enterprise AI inference services and model registry capabilities. Enable generative AI applications using foundation models, RAG, and vector databases; collaborate with frontend, data scientists, product, and UX teams to drive production-ready AI platform features on Kubernetes-based microservices.

The Data/AI Cloud Engineer will implement AWS data services, build ETL pipelines, optimize databases, and support data-driven solutions collaborating with technical teams.

The Principal Software Engineer will lead the architecture and development of Redpanda's Agentic Data Plane, focusing on integrating AI agents with enterprise data, improving system observability, and engaging with strategic customers.